This article is a community submission. The author is Chike Okonkwo, co-founder at Web3 gaming social media protocol Gamic HQ.
The views expressed in this article are those of the contributor/author and do not necessarily reflect those of Binance Academy.
TL;DR
Data tokenization is the process of converting sensitive data such as credit card information into tokens that can be securely transferred on the blockchain without revealing the original data.
Data tokenization can enhance data security, privacy, and compliance while preventing unauthorized access and misuse.
Data tokenization requires careful consideration and implementation to manage its benefits and drawbacks.
What Is a Token?
Tokens are non-mineable digital units that exist as registry entries in blockchains. Tokens come in many different forms and have numerous use cases. For instance, they can be used as currencies or to encode data.
Tokens are generally issued using blockchains such as the Ethereum blockchain and BNB Chain. Some popular token standards include ERC-20, ERC-721, ERC-1155, and BEP-20. Tokens are transferable units of value issued on top of a blockchain, but they aren’t cryptocurrency coins like bitcoin or ether that are native to the underlying blockchain.
Some tokens might be redeemable for off-chain assets such as gold and property in what’s called the tokenization of real-world assets (RWAs).
What Is Data Tokenization?
Data tokenization is the process of converting sensitive data, such as credit card information or health data, into tokens that can be transferred, stored, and processed without exposing the original data.
These tokens are usually unique, unchangeable, and can be verified on the blockchain to enhance data security, privacy, and compliance. For example, a credit card number can be tokenized into a random string of digits that can be used for payment verification without revealing the actual card number.
Data tokenization can also apply to social media accounts. Users can choose to tokenize their online presence to seamlessly move from one social media platform to another while maintaining ownership of their personal data.
The concept of data tokenization has been around for a while. It’s commonly used in the financial sector to secure payment information, but it has the potential to be applied to many more industries.
How Is Tokenization Different From Encryption?
Tokenization and encryption are methods of protecting data. However, they work in different ways and serve different purposes.
Encryption is the process of converting plaintext data into an unreadable format (ciphertext) that can only be decrypted with a secret key. It’s a mathematical process that scrambles the data, making it unreadable to anyone who doesn’t have the key. Encryption is used in various scenarios, including secure communication, data storage, authentication, digital signatures, and regulatory compliance.
Tokenization, on the other hand, is the process of replacing sensitive data with non-sensitive, unique identifiers called tokens. It doesn’t rely on a secret key to protect the data. For example, a credit card number may be replaced with a token that has no relation to the original number but can still be used to process transactions.
Tokenization is often used when data security and compliance with regulatory standards are critical, such as payment processing, healthcare and personally identifiable information management.
How Data Tokenization Works
Let’s say a user wants to switch from one social media platform to another. On traditional Web 2.0 social media platforms, the user would have to set up a new account and enter all of their personal data from scratch. It’s also likely that post history and connections on the old platform won’t move over to the new platform.
With data tokenization, users can link their existing digital identity to the new platform to transfer their personal data over automatically. To do this, the user needs to have a digital wallet like Metamask with the wallet address representing their identity on-chain.
The user must then connect the wallet with the new social media platform. Personal history, connections, and assets are automatically synced on the new platform because Metamask contains the user's digital identity and data on the blockchain.
This means any tokens, NFTs, and past transactions the user accumulated on the previous platform won’t be lost. This gives the user complete control of which platform to migrate to while not feeling restricted to a particular platform.
Benefits of Data Tokenization
Enhanced data security
Data tokenization enhances data security. By replacing sensitive data with tokens, data tokenization reduces the risk of data breaches, identity theft, fraud, and other cyberattacks. Tokens are linked to the original data with a secure mapping system, so even if the tokens are stolen or leaked, the original data remains protected.
Compliance with regulations
Many industries are subject to strict data protection regulations. Tokenization can help organizations meet these requirements by securing sensitive information and providing a solution that can reduce the chances of non-compliance. Because tokenized data is considered non-sensitive, it can also lower the complexity of security audits and simplify data management.
Secure data sharing
Tokenization could enable secure data sharing across departments, vendors, and partners by only providing access to the tokens without revealing sensitive information. Tokenization can scale efficiently to meet the growing needs of organizations while reducing the cost of implementing data security measures.
Limitations of Data Tokenization
Data quality
Tokenizing data may affect the quality and accuracy of the data, as some information may be lost or distorted during the tokenization process. For example, if a user's location is turned into a token, it might negatively impact how they can view relevant content based on location.
Data interoperability
Tokenizing data may make it difficult for different systems that use or process the data to work together. For example, tokenizing a user's email address may prevent them from receiving notifications from other platforms or services. Tokenizing a user's phone number may hinder their ability to make or receive calls or texts, depending on the platforms they use.
Data governance
Tokenizing data may raise legal and ethical questions about who owns and controls the data and how it is used and shared. Tokenizing a user's personal information, for example, could change how they express consent to how their data is collected and used. Tokenizing a user's social media posts could go against their freedom of expression or intellectual property rights.
Data recovery
Recovering data can be more complicated if a tokenization system fails. Organizations must restore both the tokenized data and the original sensitive data stored in the token vault, which can be complex.
Data Tokenization Use Case: Social Media and NFTs
Centralized social media platforms collect vast amounts of user data daily to create targeted ads, recommend content, and personalize user experiences. This information is often stored in centralized databases, which can be sold without users’ permission or hacked and compromised.
With data tokenization, users can tokenize their social media data and sell it to advertisers or researchers if they wish to do so. Users can control who can see or share their content. They can also create custom rules for their profiles and content.
For example, they can allow only verified users to view their content or set a minimum token balance for those who want to interact with them. This gives users full control of their social graph, content, and monetization channels such as tipping and subscriptions.
Closing Thoughts
Data tokenization has already been adopted in many industries, including healthcare, finance, media, and social networks. Driven by the growing need for data security and regulatory compliance, data tokenization is likely to continue to grow.
Implementing this approach effectively requires careful consideration and implementation. Data tokenization should be done in a clear and responsible manner that respects the rights and expectations of the users while complying with all relevant laws and regulations.
Further Reading
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